Drowsiness detection using fNIRS in different time windows for a passive BCI

In this research, we have investigated the detection of drowsiness activity in dorsolateral-prefrontal cortex in three different time windows (0~3 sec, 0~4 sec and 0~5 sec) using functional near-infrared spectroscopy (fNIRS). Five drowsy subjects participated in a simulated driving task while their brain activity is monitored using fNIRS. The recorded brain activity is segmented into three windows for the acquisition of signal mean, signal slope and number of peaks as features. The data in each window is classified using linear discriminant analysis to find best window size. The results show that the best accuracy is obtained using 0~5 sec window after classification. Although the classification accuracy in 0~4 sec window is lower than in 0~5 sec window, both accuracies are suitable for brain-computer interface applications (i.e. accuracy>70%). The accuracy in 0~3 sec window is less than 70% for two subjects. For driver drowsiness detection, high accuracy with quick detection time is required, therefore we propose drowsiness detection in 0~4 sec window using fNIRS monitoring.

[1]  S. Sul,et al.  Anti-Sway Control of Container Cranes: Inclinometer, Observer, and State Feedback , 2004 .

[2]  Keum-Shik Hong,et al.  Passive BCI based on drowsiness detection: an fNIRS study. , 2015, Biomedical optics express.

[3]  Keum-Shik Hong,et al.  Modified Skyhook Control of Semi-Active Suspensions: A New Model, Gain Scheduling, and Hardware-in-the-Loop Tuning , 2002 .

[4]  Keum-Shik Hong,et al.  Improving classification accuracy of covert yes/no response decoding using support vector machines: An fNIRS study , 2014, 2014 International Conference on Robotics and Emerging Allied Technologies in Engineering (iCREATE).

[5]  Chun-Hsiang Chuang,et al.  Wireless and Wearable EEG System for Evaluating Driver Vigilance , 2014, IEEE Transactions on Biomedical Circuits and Systems.

[6]  Keum-Shik Hong,et al.  A PC-based open robot control system: PC-ORC , 2001, ISIE 2001. 2001 IEEE International Symposium on Industrial Electronics Proceedings (Cat. No.01TH8570).

[7]  Wan-Young Chung,et al.  Mobile Healthcare for Automatic Driving Sleep-Onset Detection Using Wavelet-Based EEG and Respiration Signals , 2014, Sensors.

[8]  Suzanne Kieffer,et al.  Feature extraction and selection for objective gait analysis and fall risk assessment by accelerometry , 2011, Biomedical engineering online.

[9]  K. Hong,et al.  CLASSIFYING MENTAL ACTIVITIES FROM EEG-P 300 SIGNALS USING ADAPTIVE NEURAL NETWORKS , 2012 .

[10]  Y. Kim,et al.  Classification of prefrontal and motor cortex signals for three-class fNIRS–BCI , 2015, Neuroscience Letters.

[11]  Klaus-Robert Müller,et al.  Enhanced Performance by a Hybrid Nirs–eeg Brain Computer Interface , 2022 .

[12]  M. R. Bhutta,et al.  Note: three wavelengths near-infrared spectroscopy system for compensating the light absorbance by water. , 2014, The Review of scientific instruments.

[13]  J. Horne,et al.  Vehicle accidents related to sleep: a review. , 1999, Occupational and environmental medicine.

[14]  Keum-Shik Hong,et al.  Real-time feature extraction of P300 component using adaptive nonlinear principal component analysis , 2011, Biomedical engineering online.

[15]  P. Caffier,et al.  Experimental evaluation of eye-blink parameters as a drowsiness measure , 2003, European Journal of Applied Physiology.

[16]  Zhiwei Zhu,et al.  Real-time nonintrusive monitoring and prediction of driver fatigue , 2004, IEEE Transactions on Vehicular Technology.

[17]  Keum Shik Hong,et al.  Navigation Function-Based Control of Multiple Wheeled Vehicles , 2011, IEEE Transactions on Industrial Electronics.

[18]  Keum-Shik Hong,et al.  Reduction of physiological effects in fNIRS waveforms for efficient brain-state decoding , 2014, Neuroscience Letters.

[19]  Andrzej Cichocki,et al.  Bimodal BCI Using Simultaneously NIRS and EEG , 2014, IEEE Transactions on Biomedical Engineering.

[20]  S. Ge,et al.  Recognition of stimulus-evoked neuronal optical response by identifying chaos levels of near-infrared spectroscopy time series , 2011, Neuroscience Letters.

[21]  Eric Laciar,et al.  Automatic detection of drowsiness in EEG records based on multimodal analysis. , 2014, Medical engineering & physics.

[22]  K. Hong,et al.  A Feedback Linearization Control of Container Cranes: Varying Rope Length , 2007 .

[23]  M. Toichi,et al.  Dorsolateral prefrontal cortical oxygenation during REM sleep in humans , 2011, Brain Research.

[24]  Keum-Shik Hong,et al.  fNIRS based dual movement control command generation using prefrontal brain activity , 2014, 2014 International Conference on Robotics and Emerging Allied Technologies in Engineering (iCREATE).

[25]  Keum-Shik Hong,et al.  Decoding Answers to Four-Choice Questions Using Functional near Infrared Spectroscopy , 2015 .

[26]  Keum-Shik Hong,et al.  Modeling and Automatic Feedback Control of Tremor: Adaptive Estimation of Deep Brain Stimulation , 2013, PloS one.

[27]  Keum-Shik Hong,et al.  Decoding of four movement directions using hybrid NIRS-EEG brain-computer interface , 2014, Front. Hum. Neurosci..

[28]  Keum-Shik Hong,et al.  Input shaping control of a nuclear power plant’s fuel transport system , 2014 .

[29]  S. Coyle,et al.  Brain–computer interfaces: a review , 2003 .

[30]  Keum Shik Hong,et al.  Reduction of Delay in Detecting Initial Dips from Functional Near-Infrared Spectroscopy Signals Using Vector-Based Phase Analysis , 2016, Int. J. Neural Syst..

[31]  Keum Shik Hong,et al.  Sliding-mode and proportional-derivative-type motion control with radial basis function neural network based estimators for wheeled vehicles , 2014, Int. J. Syst. Sci..

[32]  Keum-Shik Hong,et al.  Reduction of trial-to-trial variability in functional near-infrared spectroscopy signals by accounting for resting-state functional connectivity , 2013, Journal of biomedical optics.

[33]  K. Hong,et al.  Decoding four different sound-categories in the auditory cortex using functional near-infrared spectroscopy , 2016, Hearing Research.

[34]  Keum-Shik Hong,et al.  Direct adaptive control of parabolic systems: algorithm synthesis, and convergence and stability analysis , 1993, Proceedings of 32nd IEEE Conference on Decision and Control.

[35]  K. Hong,et al.  Lateralization of music processing with noises in the auditory cortex: an fNIRS study , 2014, Front. Behav. Neurosci..

[36]  Keum-Shik Hong,et al.  Single-trial lie detection using a combined fNIRS-polygraph system , 2015, Front. Psychol..

[37]  Keum-Shik Hong,et al.  fNIRS-based brain-computer interfaces: a review , 2015, Front. Hum. Neurosci..

[38]  M. R. Bhutta,et al.  Water correction algorithm to improve the classification accuracy: A near-infrared spectroscopy study , 2014, 2014 International Conference on Robotics and Emerging Allied Technologies in Engineering (iCREATE).

[39]  Jens Steinbrink,et al.  Decoding Vigilance with NIRS , 2014, PloS one.

[40]  Keum-Shik Hong,et al.  Online binary decision decoding using functional near-infrared spectroscopy for the development of brain–computer interface , 2014, Experimental Brain Research.

[41]  Keum-Shik Hong,et al.  Noise reduction in functional near-infrared spectroscopy signals by independent component analysis. , 2013, The Review of scientific instruments.

[42]  K. Hong,et al.  Robust adaptive boundary control of an axially moving string under a spatiotemporally varying tension , 2004 .